People and pharmaceutical companies around the world are increasingly challenged by antibiotic-resistant bacteria. The discovery of new drugs to fight these bugs, meanwhile, can be a slow, costly process as companies must make sure the drugs are effective and safe. It currently takes on average 10 years and more than $2 billion to create a new drug and get it on the market.
An interdisciplinary LSU team led by Supratik Mukhopadhyay, associate professor in the department of computer science, and Michal Brylinski, associate professor in the department of biological sciences, is suggesting using artificial intelligence, or AI, to solve this problem, LSU announced today.
The LSU team is a semifinalist for the IBM Watson AI XPRIZE, a $3 million cash prize to be used in research funding. In their research, they are using computer learning, or artificial intelligence, and datasets of known chemical compounds to teach their AI program to pinpoint compounds that could be effective against specific bacteria. From there, the compounds could be used to create new medicines.
The IBM Watson AI XPRIZE is a global competition encouraging teams of researchers to develop powerful applications based on artificial intelligence. As semifinalists, the LSU team will receive a $15,000 milestone award on its way toward the $3 million grand prize, which will be awarded to one of the 10 teams now remaining among the original 147 in 2016. The second- and third-place teams will receive $1 million and $500,000, respectively.
Brylinski compares the team’s use of AI for drug discovery to that of engineers of self-driving cars.
“In cars, the AI gets lots of data from sensors and then has to make decisions about when to stop or when to accelerate,” he says. “We’re doing something very similar. We’re collecting lots of data from experiments to train our AI to be able to make good decisions, whether to synthesize a drug or not, and knowing if a particular drug is going to be effective.” Read the full LSU announcement.